1. |
- Bar, N., et al.
(författare)
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A reference map of potential determinants for the human serum metabolome
- 2020
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Ingår i: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
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Tidskriftsartikel (refereegranskat)abstract
- The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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2. |
- Speliotes, Elizabeth K., et al.
(författare)
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Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
- 2010
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 937-948
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Tidskriftsartikel (refereegranskat)abstract
- Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ~2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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3. |
- Heid, Iris M, et al.
(författare)
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Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
- 2010
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 949-960
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Tidskriftsartikel (refereegranskat)abstract
- Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
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4. |
- Willer, Cristen J., et al.
(författare)
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Six new loci associated with body mass index highlight a neuronal influence on body weight regulation
- 2009
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 41:1, s. 25-34
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Tidskriftsartikel (refereegranskat)abstract
- Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
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5. |
- Lango Allen, Hana, et al.
(författare)
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Hundreds of variants clustered in genomic loci and biological pathways affect human height.
- 2010
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 467:7317, s. 832-8
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Tidskriftsartikel (refereegranskat)abstract
- Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
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6. |
- Obura, M., et al.
(författare)
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Clinical profiles of post-load glucose subgroups and their association with glycaemic traits over time : An IMI-DIRECT study
- 2021
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Ingår i: Diabetic Medicine. - : Wiley. - 0742-3071 .- 1464-5491. ; 38:2
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To examine the hypothesis that, based on their glucose curves during a seven-point oral glucose tolerance test, people at elevated type 2 diabetes risk can be divided into subgroups with different clinical profiles at baseline and different degrees of subsequent glycaemic deterioration. Methods: We included 2126 participants at elevated type 2 diabetes risk from the Diabetes Research on Patient Stratification (IMI-DIRECT) study. Latent class trajectory analysis was used to identify subgroups from a seven-point oral glucose tolerance test at baseline and follow-up. Linear models quantified the associations between the subgroups with glycaemic traits at baseline and 18 months. Results: At baseline, we identified four glucose curve subgroups, labelled in order of increasing peak levels as 1–4. Participants in Subgroups 2–4, were more likely to have higher insulin resistance (homeostatic model assessment) and a lower Matsuda index, than those in Subgroup 1. Overall, participants in Subgroups 3 and 4, had higher glycaemic trait values, with the exception of the Matsuda and insulinogenic indices. At 18 months, change in homeostatic model assessment of insulin resistance was higher in Subgroup 4 (β = 0.36, 95% CI 0.13–0.58), Subgroup 3 (β = 0.30; 95% CI 0.10–0.50) and Subgroup 2 (β = 0.18; 95% CI 0.04–0.32), compared to Subgroup 1. The same was observed for C-peptide and insulin. Five subgroups were identified at follow-up, and the majority of participants remained in the same subgroup or progressed to higher peak subgroups after 18 months. Conclusions: Using data from a frequently sampled oral glucose tolerance test, glucose curve patterns associated with different clinical characteristics and different rates of subsequent glycaemic deterioration can be identified.
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7. |
- Allesøe, Rosa Lundbye, et al.
(författare)
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Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
- 2023
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 41:3, s. 399-408
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Tidskriftsartikel (refereegranskat)abstract
- The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.
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8. |
- Loos, Ruth J. F., et al.
(författare)
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Common variants near MC4R are associated with fat mass, weight and risk of obesity
- 2008
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 40:6, s. 768-775
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Tidskriftsartikel (refereegranskat)abstract
- To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.
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10. |
- Tura, Andrea, et al.
(författare)
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Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT : An IMI DIRECT Study
- 2021
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Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 70:9, s. 2092-2106
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Tidskriftsartikel (refereegranskat)abstract
- Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.
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11. |
- Bizzotto, Roberto, et al.
(författare)
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Processes Underlying Glycemic Deterioration in Type 2 Diabetes : An IMI DIRECT Study
- 2021
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 44:2, s. 511-518
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS: Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS: Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.
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12. |
- Brown, A.A., et al.
(författare)
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Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue. © 2023, Springer Nature Limited.
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13. |
- Geidenstam, N., et al.
(författare)
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Metabolite profiling of obese individuals before and after a one year weight loss program
- 2017
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Ingår i: International Journal of Obesity. - : Springer Science and Business Media LLC. - 0307-0565 .- 1476-5497. ; 41:9, s. 1369-1378
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Tidskriftsartikel (refereegranskat)abstract
- Objective:We and others have previously characterized changes in circulating metabolite levels following diet-induced weight loss. Our aim was to investigate whether baseline metabolite levels and weight-loss-induced changes in these are predictive of or associated with changes in body mass index (BMI) and metabolic risk traits.Methods:Serum metabolites were analyzed with gas and liquid chromatography/mass spectrometry in 91 obese individuals at baseline and after participating in a 1 year non-surgical weight loss program.ResultsA total of 137 metabolites were identified and semi-quantified at baseline (BMI 42.7±5.8, mean±s.d.) and at follow-up (BMI 36.3±6.6). Weight-loss-induced modification was observed for levels of 57 metabolites in individuals with â
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14. |
- Geidenstam, Nina, et al.
(författare)
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Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain
- 2019
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 14:9
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Tidskriftsartikel (refereegranskat)abstract
- Background Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. Methods and results Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10−8) and 5 suggestively (p < 1 × 10−6) significant loci, several of which have been previously linked to obesity-related phenotypes. Conclusions We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.
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15. |
- Obura, Morgan, et al.
(författare)
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Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes : An IMI-DIRECT study
- 2020
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:11
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Tidskriftsartikel (refereegranskat)abstract
- AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.
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18. |
- Atabaki-Pasdar, Naeimeh, et al.
(författare)
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Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study
- 2021
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.Competing Interest StatementHR is an employee and shareholder of Sanofi. MIM: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MIM has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MIM is an employee of Genentech, and a holder of Roche stock. AM is a consultant for Lilly and has received research grants from several diabetes drug companies. PWF has received research grants from numerous diabetes drug companies and fess as consultant from Novo Nordisk, Lilly, and Zoe Global Ltd. He is currently the Scientific Director in Patient Care at the Novo Nordisk Foundation. Other authors declare non competing interests.Funding StatementThe work leading to this publication has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement 115317 (DIRECT) resources of which are composed of financial contribution from the European Union Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. NAP is supported in part by Henning och Johan Throne-Holsts Foundation, Hans Werthen Foundation, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. HPM is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AGJ is supported by an NIHR Clinician Scientist award (17/0005624). RK is funded by the Novo Nordisk Foundation (NNF18OC0031650) as part of a postdoctoral fellowship, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AK, PM, HF, JF and GNG are supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. TJM is funded by an NIHR clinical senior lecturer fellowship. S.Bru acknowledges support from the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). ATH is a Wellcome Trust Senior Investigator and is also supported by the NIHR Exeter Clinical Research Facility. JMS acknowledges support from Science for Life Laboratory (Plasma Profiling Facility), Knut and Alice Wallenberg Foundation (Human Protein Atlas) and Erling-Persson Foundation (KTH Centre for Precision Medicine). MIM is supported by the following grants; Wellcome (090532, 098381, 106130, 203141, 212259); NIH (U01-DK105535). PWF is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Approval for the study protocol was obtained from each of the regional research ethics review boards separately (Lund, Sweden: 20130312105459927, Copenhagen, Denmark: H-1-2012-166 and H-1-2012-100, Amsterdam, Netherlands: NL40099.029.12, Newcastle, Dundee and Exeter, UK: 12/NE/0132), and all participants provided written informed consent at enrolment. The research conformed to the ethical principles for medical research involving human participants outlined in the Declaration of Helsinki.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAuthors agree to make data and materials supporting the results or analyses presented in their paper available upon reasonable request
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20. |
- Jendle, Johan, 1963-, et al.
(författare)
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Willingness to pay for diabetes drug therapy in type 2 diabetes patients : based on LEAD clinical programme results
- 2012
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Ingår i: Journal of Medical Economics. - Oxfordshire, United Kingdom : Taylor & Francis. - 1369-6998 .- 1941-837X. ; 15:Suppl 2, s. 1-5
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The purpose of this study was to investigate the preferences of people with diabetes for liraglutide vs other glucose lowering drugs, based on outcomes of clinical trials.Methods: Willingness to pay (WTP) for diabetes drug treatment was assessed by combining results from a recent WTP study with analysis of results from the Liraglutide Effect and Action in Diabetes (LEAD) programme. The LEAD programme included six randomised clinical trials with 3967 participants analysing efficacy and safety of liraglutide 1.2 mg (LEAD 1-6 trials), rosiglitazone (LEAD 1 trial), glimepiride (LEAD 2-3 trials), insulin glargine (LEAD 5 trial), and exenatide (LEAD 6 trial). The WTP survey used discrete choice experimental (DCE) methodology to evaluate the convenience and clinical effects of glucose lowering treatments.Results: People with type 2 diabetes were prepared to pay an extra €2.64/day for liraglutide compared with rosiglitazone, an extra €1.94/day compared with glimepiride, an extra €3.36/day compared with insulin glargine, and an extra €0.81/day compared with exenatide. Weight loss was the largest component of WTP for liraglutide compared with rosiglitazone, glimepiride, and insulin glargine. Differences in the administration of the two drugs was the largest component of WTP for liraglutide (once daily anytime) compared with exenatide (twice daily with meals). A limitation of the study was that it was based on six clinical trials where liraglutide was the test drug, but each trial had a different comparator, therefore the clinical effects of liraglutide were much better documented than the comparators.Conclusions: WTP analyses of the clinical results from the LEAD programme suggested that participants with type 2 diabetes were willing to pay appreciably more for liraglutide than other glucose lowering treatments. This was driven by the relative advantage of weight loss compared with rosiglitazone, glimepiride, and insulin glargine, and administration frequency compared with exenatide.
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21. |
- Jendle, Johan, 1963-, et al.
(författare)
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Willingness to pay for health improvements associated with anti-diabetes treatments for people with type 2 diabetes
- 2010
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Ingår i: Current Medical Research and Opinion. - : Informa Healthcare. - 1473-4877 .- 0300-7995. ; 26:4, s. 917-923
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: This study aimed to investigate the most important consequences of diabetes medication, as measured by the patients' willingness to pay (WTP). Research design and methods: People in Sweden were recruited using existing nationwide e-mail panels if they were adults (>= 18 years) with type 2 diabetes and were receiving pharmacological anti-diabetes treatment(s). Data were collected electronically and results were analysed using a standard statistical model designed for choice games (conditional logit). Six characteristics relating to treatment of diabetes were examined: weight (gain or loss), mean glycated haemoglobin level (HbA(1c)), hypoglycaemic events, nausea, need for injections (with or independently of meals), and blood glucose testing. Results: A total of 461 people with type 2 diabetes (291 males; 170 females) completed an internet questionnaire and were eligible for inclusion. Participants placed high value on weight loss and nausea avoidance; they would pay 176 Swedish Krona (SEK)/(sic)15.61 per month to lose 1 kg, and would pay SEK 560 ((sic)49.67) per month to avoid nausea completely. Patients wanting to reduce the number of hypoglycaemic events from three per month to none were willing to pay SEK 419 ((sic)37.17) per month. Patients valued a 1 percentage point reduction in HbA(1c) at SEK 414 ((sic)36.72) per month. Participants preferred taking tablets to injections and required a compensation of SEK 376 ((sic)33.35) to accept one injection/day. Injections independent of meals were preferred to injections with meals (WTP: SEK 140/(sic)12.42 per month). Potential limitations of this study are that the preferences expressed may not match preferences in real-life situations, and bias through the use of electronic questionnaire, which restricted participation to those with access to, and experience with, the internet. Conclusion: People with type 2 diabetes were willing to pay a considerable amount of money each month to lose weight, reduce or avoid hypoglycaemic events and reduce HbA(1C).
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22. |
- Kotronen, A., et al.
(författare)
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A common variant in PNPLA3, which encodes adiponutrin, is associated with liver fat content in humans
- 2009
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 52:6, s. 1056-1060
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Tidskriftsartikel (refereegranskat)abstract
- It has recently been suggested that the rs738409 G allele in PNPLA3, which encodes adiponutrin, is strongly associated with increased liver fat content in three different ethnic groups. The aims of the present study were as follows: (1) to try to replicate these findings in European individuals with quantitative measures of hepatic fat content; (2) to study whether the polymorphism influences hepatic and adipose tissue insulin sensitivity; and (3) to investigate whether PNPLA3 expression is altered in the human fatty liver. We genotyped 291 Finnish individuals in whom liver fat had been measured using proton magnetic resonance spectroscopy. Hepatic PNPLA3 expression was measured in 32 participants. Hepatic and adipose tissue insulin sensitivities were measured using a euglycaemic-hyperinsulinaemic (insulin infusion 0.3 mU kg(-1) min(-1)) clamp technique combined with infusion of [3-H-3]glucose in 109 participants. The rs738409 G allele in PNPLA3 was associated with increased quantitative measures of liver fat content (p = 0.011) and serum aspartate aminotransferase concentrations (p = 0.002) independently of age, sex and BMI. Fasting serum insulin and hepatic and adipose tissue insulin sensitivity were related to liver fat content independently of genotype status. PNPLA3 mRNA expression in the liver was positively related to obesity (r = 0.62, p < 0.0001) and to liver fat content (r = 0.58, p = 0.025) in participants who were not morbidly obese (BMI < 40 kg/m(2)). A common variant in PNPLA3 increases the risk of hepatic steatosis in humans.
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23. |
- Nielsen, Rikke V., et al.
(författare)
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Personalized intervention based on early detection of atherosclerosis : JACC state-of-the-art review
- 2024
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Ingår i: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 83:21, s. 2112-2127
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Forskningsöversikt (refereegranskat)abstract
- Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide and challenges the capacity of health care systems globally. Atherosclerosis is the underlying pathophysiological entity in two-thirds of patients with CVD. When considering that atherosclerosis develops over decades, there is potentially great opportunity for prevention of associated events such as myocardial infarction and stroke. Subclinical atherosclerosis has been identified in its early stages in young individuals; however, there is no consensus on how to prevent progression to symptomatic disease. Given the growing burden of CVD, a paradigm shift is required—moving from late management of atherosclerotic CVD to earlier detection during the subclinical phase with the goal of potential cure or prevention of events. Studies must focus on how precision medicine using imaging and circulating biomarkers may identify atherosclerosis earlier and determine whether such a paradigm shift would lead to overall cost savings for global health.
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24. |
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25. |
- Safai, N., et al.
(författare)
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Effect of metformin on plasma metabolite profile in the Copenhagen Insulin and Metformin Therapy (CIMT) trial
- 2018
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Ingår i: Diabetic Medicine. - : Wiley. - 0742-3071. ; 35:7, s. 944-953
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Metformin is the first-line treatment for Type 2 diabetes. However, not all people benefit from this drug. Our aim was to investigate the effects of metformin on the plasma metabolome and whether the pretreatment metabolite profile can predict HbA1c outcome. Methods: Post hoc analysis of the Copenhagen Insulin and Metformin Therapy (CIMT) trial, a multicentre study from May 2008 to December 2012, was carried out. We used a non-target method to analyse 87 plasma metabolites in participants with Type 2 diabetes (n = 370) who were randomized in a 1: 1 ratio to 18 months of metformin or placebo treatment. Metabolites were measured by liquid chromatography-mass spectrometry at baseline and at 18-month follow-up and the data were analysed using a linear mixed-effect model. Results: At baseline, participants who were on metformin before the trial (n = 312) had higher levels of leucine/isoleucine and five lysophosphatidylethanolamines (LPEs), and lower levels of carnitine and valine compared with metformin-naïve participants (n = 58). At follow-up, participants randomized to metformin (n = 188) had elevated levels of leucine/isoleucine and reduced carnitine, tyrosine and valine compared with placebo (n = 182). At baseline, participants on metformin treatment with the highest levels of carnitine C10:1 and leucine/isoleucine had the lowest HbA1c (P-interaction = 0.02 and 0.03, respectively). This association was not significant with HbA1c at follow-up. Conclusions: Metformin treatment is associated with decreased levels of valine, tyrosine and carnitine, and increased levels of leucine/isoleucine. None of the identified metabolites can predict the HbA1c-lowering effect of metformin. Further studies of the association between metformin, carnitine and leucine/isoleucine are warranted.
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